Interpretability and Safety for Robot Foundation Models

Описание: At our inaugural YCML at Startup School, YC Partner Ankit Gupta speaks with Bear Häon about applying interpretability and AI safety techniques to vision-language-action models.

The work examines activations inside a vision-language-action model, groups neurons associated with concepts such as speed or caution, and then steers the robot's behavior by amplifying those groups. This provides a way to better understand and control how robots translate language into physical actions. The broader goal is to develop safety methods for physical AI, where failures can have direct consequences in the real world.

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